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Method for multi-channel secret information transmission through capsule network

A secret information, multi-channel technology, applied in the field of multi-channel secret information transmission through the capsule network, to achieve a strong practical effect

Pending Publication Date: 2022-04-12
SHANGHAI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In addition, the existing neural network information hiding methods are all designed for convolutional neural networks.

Method used

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  • Method for multi-channel secret information transmission through capsule network
  • Method for multi-channel secret information transmission through capsule network
  • Method for multi-channel secret information transmission through capsule network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0035] see Figure 1 ~ Figure 3 , present a method for multi-channel secret information transmission via capsule networks. It is characterized in that, during the training process of the capsule network, multiple copies of different secret information are embedded into the capsule network; each receiver can use his own key to extract the corresponding information in the capsule network, and the other parts of the secret information information, the receiver cannot determine the existence of the secret information, let alone extract it; in addition, the parameters of the information extraction network are directly generated by the key without training, so there is no need to transmit the information extraction network to the receiver, only need to hold The secret information can be extracted with the correct key;

[0036] Such as figure 2 As shown, the capsule network architecture used is composed of two convolutional layers - Conv1 layer and PrimaryCaps layer, and a fully c...

Embodiment 2

[0054] Such as figure 1 As shown, a method for multi-channel secret information transmission through capsule network. This example uses the MNIST image dataset as an example to transmit secret information to 10 recipients at the same time.

[0055] (1) Construct the capsule network architecture for information hiding as described in Architecture A.

[0056] (2) Construct 10 fully connected layers as information extraction networks for 10 receivers, and connect them to the prediction vectors of Architecture A superior.

[0057] (3) Using the key {K 1 ,K 2 ,...,K 10} respectively generate 10 fully connected layer parameters of the information extraction network. After the parameters are generated, they remain unchanged during the network training process.

[0058] (4) with {M 1 , M 2 ,...,M 10} as a guide, with the goal of minimizing the loss shown in Equation (6), Architecture B is trained using the MNIST image dataset. The architecture A obtained through training i...

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Abstract

The invention provides a method for multi-channel secret information transmission through a capsule network. A plurality of different pieces of secret information are embedded by training the same capsule network. Secret information for a plurality of recipients is embedded in a capsule network during a capsule network training process. And then, the receiver can extract corresponding information in the secret-containing capsule network by using the own secret key. And for the secret information of other parts, the receiver cannot determine the existence of the secret information and cannot extract the secret information. And the secret information is not exposed, so that the information hiding security can be ensured. The secret information is embedded in the training process of the capsule network instead of being embedded by modifying the network weight after training, so that the influence of information embedding on the original task of the network is very small. In addition, the parameters of the information extraction network are directly generated by the key and are not required to be obtained through training, so that the information extraction network does not need to be transmitted to the receiver. And secret information can be extracted only by holding a correct key.

Description

technical field [0001] The invention relates to the field of secret data transmission, in particular to a method for multi-channel secret information transmission through a capsule network. Secret information for multiple recipients is embedded in the capsule network. Afterwards, the recipient can use the key to extract the corresponding information in the network containing the capsule. As for other parts of the secret information, the recipient cannot determine the existence of the secret information, let alone extract it. Background technique [0002] In recent years, deep learning technology has been widely used in the field of artificial intelligence, such as image recognition, image semantic segmentation, natural language processing, etc. A large amount of labeled data and computing resources are used to train neural network models, such as convolutional neural networks, recurrent neural networks, generative confrontation networks, residual networks, capsule networks...

Claims

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Application Information

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IPC IPC(8): H04L9/40G06N3/08
Inventor 王子驰冯国瑞张新鹏
Owner SHANGHAI UNIV